Time-to-Event Analysis of Paclitaxel-Associated Peripheral Neuropathy in Advanced Non-Small-Cell Lung Cancer Highlighting Key Influential Treatment/Patient Factors.

Paclitaxel-associated peripheral neuropathy (PN), a major dose-limiting toxicity, significantly impacts patients' quality of life/treatment outcome. Evaluation of risk factors often ignores time of PN onset, precluding the impact of time-dependent factors, e.g., drug exposure, needed to comprehensively characterize PN. We employed parametric time-to-event (TTE) analysis to describe the time course of risk of first occurrence of clinically relevant PN grades ≥2 (PN2+, n = 105, common terminology criteria v4.0) and associated patient/treatment characteristics, leveraging data from 365 patients (1454 cycles) receiving paclitaxel every 3 weeks (plus carboplatin AUC = 6 or cisplatin 80 mg/m2) for ≤6 cycles. Paclitaxel was intravenously administered (3 hours) as standard 200-mg/m2 doses (n = 182) or as pharmacokinetic-guided dosing (n = 183). A cycle-varying hazard TTE model linking surge in hazard of PN2+ to paclitaxel administration [PN2+ proportions (i.e., cases per 1000 patients), 1st day, cycle 1: 4.87 of 1000; cycle 6: 7.36 of 1000] and linear decline across cycle (last day, cycle 1: 1.64 of 1000; cycle 6: 2.48 of 1000) adequately characterized the time-varying hazard of PN2+. From joint covariate evaluation, PN2+ proportions (1st day, cycle 1) increased by 1.00 per 1000 with 5-µmol·h/l higher paclitaxel exposure per cycle (AUC between the start and end of a cycle, most relevant covariate), 0.429 per 1000 with 5-year higher age, 1.31 per 1000 (smokers vs. nonsmokers), and decreased by 0.670 per 1000 (females vs. males). Compared to 200 mg/m2 dosing every 3 weeks, model-predicted cumulative risk of PN2+ was significantly higher (42%) with 80 mg/m2 weekly dosing but reduced by 11% with 175 mg/m2 dosing every 3 weeks. The established TTE modeling framework enables quantification and comparison of patient's cumulative risks of PN2+ for different clinically relevant paclitaxel dosing schedules, sparing patients PN2+ to improve paclitaxel therapy. SIGNIFICANCE STATEMENT: Characterization of risk factors of paclitaxel-associated peripheral neuropathy (PN) typically involves time-independent comparison of PN odds in patient subpopulations, concealing the impact of time-dependent factors, e.g., changing paclitaxel exposure, required to comprehensively characterize PN. We developed a parametric time-to-event model describing the time course in risk of clinically relevant paclitaxel-associated PN, identifying the highest risk in older male smokers with higher paclitaxel area under the plasma concentration-time curve between the start and end of a cycle. The developed framework enabled quantification of patient's risk of PN for clinically relevant paclitaxel dosing schedules, facilitating future dosing decisions.

Trimester-Specific Population Pharmacokinetics and Other Correlates of Variability in Sulphadoxine-Pyrimethamine Disposition Among Ugandan Pregnant Women.

BACKGROUND: Sulphadoxine-pyrimethamine (SP) is widely used as an intermittent preventive treatment for malaria in pregnancy (IPTp). However, pharmacokinetic studies in pregnancy show variable and often contradictory findings. We describe population and trimester-specific differences in SP pharmacokinetics among Ugandan women. METHODS: SP (three tablets) were administered to 34 nonpregnant and 87 pregnant women in the second trimester. Seventy-eight pregnant women were redosed in the third trimester. Blood was collected over time points ranging from 0.5 h to 42 days postdose. Data on the variables age, body weight, height, parity, gestational age, and serum creatinine, alanine transaminase and albumin levels were collected at baseline. Plasma drug assays were performed using high-performance liquid chromatography with ultraviolet detection. Population pharmacokinetic analysis was done using NONMEM software. RESULTS: A two-compartment model with first-order absorption and a lag time best described both the sulphadoxine and pyrimethamine data. Between trimesters, statistically significant differences in central volumes of distribution (V(2)) were observed for both drugs, while differences in the distribution half-life and the terminal elimination half-life were observed for pyrimethamine and sulphadoxine, respectively. Significant covariate relationships were identified on clearance (pregnancy status and serum albumin level) and V(2) (gestational age) for sulphadoxine. For pyrimethamine, clearance (pregnancy status and age) and V(2) (gestational age and body weight) were significant. Considering a 25 % threshold for clinical relevance, only differences in clearance of both drugs between pregnant and nonpregnant women were significant. CONCLUSION: While clinically relevant differences in SP disposition between trimesters were not seen, increased clearance with pregnancy and the increasing volume of distribution in the central compartment with gestational age lend support to the revised World Health Organization guidelines advocating more frequent dosing of SP for IPTp.

Characterizing plasma albumin concentration changes in TB/HIV patients on anti retroviral and anti -tuberculosis therapy.

PURPOSE: Plasma albumin, a biomarker for hepatic function, is reported to correspondingly decrease in concentration as disease severity increases in chronic infections including HIV and TB. Our objective was to develop a semi-mechanistic disease progression model to quantify plasma albumin concentration changes during TB and HIV therapy and identify the associated covariate factors. METHODS: Plasma albumin concentration data was collected at specified times for 3 months from 262 HIV participants receiving efavirenz based anti retroviral therapy. Of these, 158 were TB co-infected and on Rifampicin based anti -tuberculosis co-treatment. An indirect response model with zero order albumin production and first order elimination was developed in NONMEM version 7.2 to describe our data. Genotype (CYP2B6*6 and 11, CYP3A5, ABCB1c.3435C>T and ABCB1rs), TB disease status, baseline age, body weight, plasma creatinine, alanine transaminase enzyme and CD4(+) count were the potential model covariates tested. RESULTS: The proposed model successfully described plasma albumin concentration changes in the study population. There was a 10.9% and 48.6% increase in albumin production rates in HIV only and TB co-infected participants respectively. Participants co-infected with TB showed a 44.2% lower baseline albumin secretion rate than those without TB while ABCB1c.3435C>T mutation was associated with a 16% higher steady state albumin secretion rate following treatment. CONCLUSION: A semi-mechanistic model describes plasma albumin concentration changes in HIV patients on ART. Further work is required to establish the utility of the model in monitoring disease progression and predicting prognosis in HIV and TB co-infected patients in absence of or during treatment.